The quality of geospatial data collection depends, among other things, on the reliability and efficiency of the GNSS receivers or even better integrated GNSS/INS systems used for positioning. ...High-precision positioning is currently not only the domain of professional receivers but can also be achieved by using simple devices, including smartphones. This research focused on the quality of 2D and 3D kinematic positioning of different geodetic and low-cost GNSS devices, using the professional mobile mapping system (MMS) as a reference. Kinematic positioning was performed simultaneously with a geodetic Septentrio AsteRx-U receiver, two u-blox receivers—ZED-F9P and ZED-F9R—and a Xiaomi Mi 8 smartphone and then compared with an Applanix Corporation GPS/INS MMS reference trajectory. The field tests were conducted in urban and non-urban environments with and without obstacles, on road sections with large manoeuvres and curves, and under overpasses and tunnels. Some general conclusions can be drawn from the analysis of the different scenarios. As expected, some results in GNSS positioning are subject to position losses, large outliers and multipath effects; however, after removing them, they are quite promising, even for the Xiaomi Mi8 smartphone. From the comparison of the GPS and GNSS solutions, as expected, GNSS processing achieved many more solutions for position determination and allowed a relevant higher number of fixed ambiguities, even if this was not true in general for the Septentrio AsteRx-U, in particular in a surveyed non-urban area with curves and serpentines characterised by a reduced signal acquisition. In GNSS mode, the Xiaomi Mi8 smartphone performed well in situations with a threshold of less than 1 m, with the percentages varying from 50% for the urban areas to 80% for the non-urban areas, which offers potential in view of future improvements for applications in terrestrial navigation.
Uncrewed aerial vehicles (UAVs) carrying sensors, such as light detection and ranging (LiDAR) and multiband cameras georeferenced by an onboard global navigation satellite system/inertial navigation ...system (GNSS/INS), have become a popular means to quickly acquire near-proximal agricultural remote sensing data. These platforms have bridged the gap between high-altitude airborne and ground-based measurements. UAV data acquisitions also allow for surveying remote sites that are logistically difficult to access from ground. With that said, deriving well-georeferenced mapping products from these mobile mapping systems is contingent on accurate determination of platform trajectory along with intersensor positional and rotational relationships, that is, the mounting parameters of various sensors with respect to the GNSS/INS unit. Conventional techniques for estimating LiDAR mounting parameters (also referred to as LiDAR system calibration) require carefully planned trajectory and target configuration. Such techniques are time-consuming, and in certain cases, not feasible to accomplish. In this article, an in-situ system calibration and trajectory enhancement strategy for UAV LiDAR is proposed. The strategy uses planting geometry in mechanized agricultural fields through an automated procedure for feature extraction/matching and using them to enhance the quality of LiDAR-derived point clouds. The proposed approach is qualitatively and quantitatively evaluated using calibration datasets as well as separately acquired validation datasets to demonstrate the performance of the developed procedure. Quantitatively, the accuracy of the resulting UAV point clouds after system calibration and an accompanying trajectory enhancement improved from as much as 43 to 4 cm.
The integration of three-dimensional (3D) data defined in different coordinate systems requires the use of well-known registration procedures, which aim to align multiple models relative to a common ...reference frame. Depending on the achieved accuracy of the estimated transformation parameters, the existing registration procedures are classified as either coarse or fine registration. Coarse registration is typically used to establish a rough alignment between the involved point clouds. Fine registration starts from coarsely aligned point clouds to achieve more precise alignment of the involved datasets. In practice, the acquired/derived point clouds from laser scanning and image-based dense matching techniques usually include an excessive number of points. Fine registration of huge datasets is time-consuming and sometimes difficult to accomplish in a reasonable timeframe. To address this challenge, this paper introduces two down-sampling approaches, which aim to improve the efficiency and accuracy of the iterative closest patch (ICPatch)-based fine registration. The first approach is based on a planar-based adaptive down-sampling strategy to remove redundant points in areas with high point density while keeping the points in lower density regions. The second approach starts with the derivation of the surface normals for the constituents of a given point cloud using their local neighborhoods, which are then represented on a Gaussian sphere. Down-sampling is ultimately achieved by removing the points from the detected peaks in the Gaussian sphere. Experiments were conducted using both simulated and real datasets to verify the feasibility of the proposed down-sampling approaches for providing reliable transformation parameters. Derived experimental results have demonstrated that for most of the registration cases, in which the points are obtained from various mapping platforms (e.g., mobile/static laser scanner or aerial photogrammetry), the first proposed down-sampling approach (i.e., adaptive down-sampling approach) was capable of exceeding the performance of the traditional approaches, which utilize either the original or randomly down-sampled points, in terms of providing smaller Root Mean Square Errors (RMSE) values and a faster convergence rate. However, for some challenging cases, in which the acquired point cloud only has limited geometric constraints, the Gaussian sphere-based approach was capable of providing superior performance as it preserves some critical points for the accurate estimation of the transformation parameters relating the involved point clouds.
The research scope of this reprint mainly focuses on GNSS data processing methods; GNSS applications; precise GNSS positioning and navigation; theories, models, and methods for processing wojGNSS ...errors; multi-GNSS positioning technologies; positioning and navigation methods under challenging environments; and low-cost GNSS positioning and navigation.
High-definition mapping of 3D lane lines has been widely needed for the highway documentation and intelligent navigation of autonomous systems. A mobile mapping system (MMS) captures both accurate 3D ...LiDAR point clouds and high-resolution images of lane markings at highway driving speeds, providing an abundant data source for combined lane mapping. This paper aims to map lanes with an MMS. The main contributions of this paper include the following: (1) an intensity correction method was introduced to eliminate the reflectivity inconsistency of road-surface LiDAR points; (2) a self-adaptive thresholding method was developed to extract lane markings from their complicated surroundings; and (3) a LiDAR-guided textural saliency analysis of MMS images was proposed to improve the robustness of lane mapping. The proposed method was tested with a dataset acquired in Wuhan, Hubei, China, which contained straight roads, curved roads, and a roundabout with various pavement markings and a complex roadside environment. The experimental results achieved a recall of 96.4%, a precision of 97.6%, and an F-score of 97.0%, demonstrating that the proposed method has strong mapping ability for various urban roads.
AbstractThis study presents an automatic method for horizontal curve identification and measurement using a mobile mapping system (MMS) with consideration of the impacts of vehicle wandering on the ...measurement. The hierarchical cluster model combined with the linear fit analysis achieved the automatic point of curvature (PC) and point of tangent (PT) station detection. The arc length method and chord offset method combined with the vehicle trajectory data were utilized for curve radius calculation. Finally, according to the adjacency patterns of the single curves, the types of curve were detected. A case study on a 9.756-km road section is provided, and on the test section, 21 single curves were detected and measured. Among them, 12 single curved segments were the simple curves, and nine single curved segments formed four reverse curves. A validation test based on the field measurement was conducted. The test results showed that the average errors for automatic PC/PT station detection, curve length measurement, and curve radius measurement were 2.15, 3.07, and 4.93%, respectively, which demonstrated that the presented method had a high accuracy for horizontal curve measurement. The significance of the proposed method was threefold. First, it solved the common problems of vehicle wandering on mobile survey. Second, it detected the curve types and the PC station of two adjacent single curves. Third, it had high accuracy, effectiveness, and automaticity, and can be used for roadway survey at network level.
Nowadays, most of the mobile mapping systems use GNSS/INS positioning technology and two-dimensional sensors to construct maps, self-localize, and gather environmental information, as well. Several ...problems can arise with traditional architectures of these systems, especially in situations where the GNSS signal is unavailable or multiple paths are involved, such as reliability issues and poor accuracy. Moreover, their cost of up to 2 million USD still poses a significant challenge for the development of new GIS applications. This paper proposes a new design of a mobile mapping system that incorporates a 1.5 cm accurate 3D LiDAR sensor and a high accuracy positioning system based on SPAN/TerraStar C-PRO technologies. The Extended Kalman Filter was used in this research to reduce the impact of GNSS signal loss by combining the SLAM method with SPAN/TerraStar C-PRO technologies. In the experiments, the concept of our mobile mapping platform was validated using the simulation environment Gazebo. So as to evaluate the proposed platform, a real dataset was collected from a complex environment where the GNSS signal is rarely available, exactly, from the campus of Moncton -Université de Moncton. The obtained results disclosed that the proposed platform proves its performance in terms of accuracy and reliability. Due to the integration of SLAM algorithm with SPAN/TerraStarC-PRO technologies, the generated 3D point cloud map includes a number of 285 million points with an mean accuracy 0.28 m even in the case of GNSS signal loss.
Historical monuments represent a cultural heritage that humanity has a duty to preserve and conserve. Lately all over the world, scanning these heritage objectives has become a priority, in order to ...preserve in the smallest details the used architecture. The work aims to complete the cultural heritage for Sânmihaiu Român hydro technical development built between 1912 and 1915, located on the Bega River in Western Romania, through modern mobile scanning technology, Leica Pegasus Backpack, necessary for the creation of a three-dimensional (3D) documentation, for the completion of the cultural heritage, and for the creation of a 3D database. The purpose of the scientific paper is restoring Sanmihaiu Roman Hidro technical Node, subject to degradation, in order to achieve the project “The navigable Bega”, waterway connection to Serbia. Collecting method of LiDAR data is Fused Slam, the acquisition of RINNEX data being made by placing a Leica GS08 Master Station. Visualization of quality graphics has been performed in Quality Control (QC) Tools. The scanning accuracy is between 2 and 3 cm and the 3D data processing was performed with the Cyclone Model version program, with SmartPick Point and Virtual Surveyor functions. The obtained point clouds will be of a great help in order to follow in time the construction which can be used whenever it will be needed by the designers and specialists in the field of hydrotechnics.
A mobile mapping system MMS is a combination of several modern sensors and is capable of acquiring meticulous spatial information in a fast and automatic manner. However, the result obtained is ...highly dependent on the quality of the global navigation satellite system GNSS which is expected to constantly provide accurate positioning solutions for the system. As a consequence, in an urban or mountainous area where satellite signals are frequently obstructed by local topography, the reliability of a terrestrial MMS system is not always guaranteed. In this study, a rigorous approach for predicting GNSS satellite reception under topographic obstructions along an MMS surveyed path is developed. By utilising a digital terrain model and a lineofsight analysis, visible satellites for a moving platform are identified and used for estimating positioning quality under a GNSS relative positioning model. Based on the results from real case studies, it is illustrated that the proposed approach provides a reliable prediction for GNSS satellite obstruction and relative positioning quality. Consequently, the locations andor epochs associated with poor GNSS positioning qualities can be identified beforehand and an appropriate survey schedule can thus be arranged.
The available sight distance (ASD) is that part of the roadway ahead which is visible to the driver, and should be of sufficient length to allow a vehicle traveling at the designated speed to stop ...before reaching a stationary object in its path. It is fundamental in assessing road safety of a project or on an existing road section. Unfortunately, an accurate estimation of the available sight distance is still an issue on existing roads, above all due to the lack of information regarding the as-built condition of the infrastructure. Today, the geomatics field already offers different solutions for collecting 3D information about environments at different scales, integrating multiple sensors, but the main issue regarding existing mobile mapping systems (MMSs) is their high cost. The first part of this research focused on the use of a low-cost MMS as an alternative for obtaining 3D information about infrastructure. The obtained model can be exploited as input data of specific algorithms, both on a GIS platform and in a numerical computing environment to estimate ASD on a typical urban road. The aim of the investigation was to compare the performances of the two approaches used to evaluate the ASD, capturing the complex morphology of the urban environment.
PDF
